System and method for performing segmentation-based enhancements of a video image

ABSTRACT

There is disclosed an apparatus for performing segmentation-based enhancements of a video image. The apparatus comprises: 1) an input buffer for storing video frames of an incoming video signal; 2) a segmentation controller capable of segmenting a first stored frame into a plurality of segments, each of the plurality of segments comprising a plurality of pixels having at least one common property; 3) an image processor capable of calculating a probability function associated with at least one pixel in the first stored frame, the probability function indicating a probability that the at least one pixel belongs within a first selected one of the plurality of segments; and 4) an enhancement controller capable of enhancing a parameter of the at least one pixel as a function of the probability function of the at least one pixel.

TECHNICAL FIELD OF THE INVENTION

The present invention is directed to an apparatus and method forenhancing a video signal and, more specifically, to an apparatus andmethod for selectively applying continuously varying amounts of videoenhancement to groups of pixels based on a probability function.

BACKGROUND OF THE INVENTION

The television industry is undergoing significant changes as a result ofthe transition from the current standard definition television (SDTV) tohigh definition television (HDTV). Much of this change is driven by theFCC requirement that all broadcasters in the United States must transmitall programming content as HDTV signals and must cease transmitting SDTVsignals by the year 2006. As a result, high definition televisions arebecoming increasingly available in the marketplace, as are HDTVconversion systems that convert an HDTV signal to an SDTV image fordisplay on a standard definition television.

Some of the driving forces behind the transition to HDTV are thepossibility of a larger and clearer picture, the changed aspect ratio(similar to movie format) in some systems, and the decreasedsusceptibility of the digital signal to noise during transmission to theviewer. As screens grow larger, viewers expect increased resolution. Fora number of years to come, however, HDTV sets must be able to receiveand display television signals according to the existing SDTV standard(e.g., PAL, NTSC, SECAM) while broadcast facilities are making thetransition to the new HDTV standard (ATSC). In the interim, it is highlydesirable that an HDTV set be able to display an SDTV signal atincreased resolution to create the subjective impression of a highdefinition television image. In addition, from the broadcast side,techniques are needed which can up-convert existing standard definition(SD) materials into high definition (HD) format.

Unfortunately, the resolution of the video signal at the televisionreceiver is limited by the quality of the original video signal (e.g.,PAL, NTSC, SECAM) or the bandwidth of the transmission channel.Therefore, in order to increase the resolution of the SDTV signals forbetter perceptual quality, post-processing the video signal in thereceiver after demodulation becomes increasingly important.

Segmentation of television images is a post-processing technique whereineach frame of an image sequence is subdivided into regions or segments.Each segment is a cluster of pixels encompassing a region of the imagewith a commonality of properties. For example, a segment may bedistinguished by a common color, a common texture, a particular shape,an amplitude range or a temporal variation. Known early applications ofsegmentation include pattern recognition, target tracking, and securitysurveillance. Most recent research into segmentation has been inapplications related to the MPEG-4 and MPEG-7 standards. In the formercase, segments are identified and uniquely encoded to achieve datecompression. In the case of MPEG-7, segmentation is used to identifyimage components for image classification and retrieval.

In the case of television image enhancement, known enhancementtechniques include both global and local enhancement methods. Examplesof global enhancement techniques may include the brightness and contrastcontrols of television (TV) receivers that control the DC offset andsignal gain globally (or uniformly) over the entire image. An example ofa local control enhancement technique is edge enhancement, in which animage processor automatically detects the location of edges in the imageand applies appropriate enhancement only in the local region of theedge.

Although local enhancement techniques are applied only to local regionsof an image, the conventional methods are nonetheless controlled byglobal parameters. In the case of edge enhancement, for example, theedge enhancement algorithm may adapt to the local edge characteristics.However, the parameters that govern the algorithm are global (i.e., theyare the same for every region of the image). The use of globalparameters places a limitation on the most effective enhancement thatcan be applied to any given image. A greater amount of enhancement wouldbe available if the enhancement algorithm could be trained to recognizethe features depicted in different segments of the image and coulddynamically choose image enhancement parameters that are optimized foreach type of image feature.

The known methods of image segmentation may be described as “hard”segmentation in that a binary decision is made. Every region eithersatisfies the relative criteria of a segment and is included in thedesired segment, or it is completely excluded. Many conventional hardsegmentation techniques are satisfactory for the applications that havebeen published in the prior art. However, these hard segmentationtechniques are not satisfactory in many advanced applications.

For example, in the case of applying hard segmentation techniques tomoving image sequences, small changes in appearance, lighting orperspective may only cause small changes is the image. The result isoften that parts of the image satisfy or fail the hard segmentationcriteria in a random way from image frame to image frame. When imageenhancement techniques are applied exclusively to the segmented regions,the result may be random variations in the enhancement, usually at theedges of the segmented regions. Such random variations in movingsequences represent disturbing artifacts that are not acceptable to theviewers.

There is therefore a need in the art for improved apparatuses andmethods for enhancing the quality of a television image. In particular,there is a need in the art for improved image enhancement techniquesthat are not affected by small variations in appearance, lighting,perspective, and the like between successive frames in a video image.More particularly, there is a need for improved apparatuses and methodsof segmenting and enhancing a video image that do not rely on hard,binary decisions regarding whether or not to apply an enhancementtechnique or a segmenting technique to a pixel or group of pixels in animage.

SUMMARY OF THE INVENTION

To address the above-discussed deficiencies of the prior art, it is aprimary object of the present invention to provide an apparatus forperforming segmentation-based enhancements of a video image. Accordingto an advantageous embodiment of the present invention, the apparatuscomprises: 1) an input buffer for storing video frames of an incomingvideo signal; 2) a segmentation controller capable of segmenting a firststored frame into a plurality of segments, each of the plurality ofsegments comprising a plurality of pixels having at least one commonproperty; 3) an image processor capable of calculating a probabilityfunction associated with at least one pixel in the first stored frame,the probability function indicating a probability that the at least onepixel belongs within a first selected one of the plurality of segments;and 4) an enhancement controller capable of enhancing a parameter of theat least one pixel as a function of the probability function of the atleast one pixel.

According to one embodiment of the present invention, the segmentationcontroller segments the first stored frame into the plurality ofsegments as a function of the probability function.

According to another embodiment of the present invention, theenhancement controller increases an amount of enhancement of theparameter as a value of the probability function increases.

According to still another embodiment of the present invention, theenhancement controller decreases an amount of enhancement of theparameter as a value of the probability function decreases.

According to yet another embodiment of the present invention, theapparatus further comprises a memory capable of storing a segmentationalgorithm, the segmentation algorithm comprising instructions executableby the segmentation controller for segmenting the first stored frameinto the plurality of segments.

According to further embodiment of the present invention, the memory isfurther capable of storing an enhancement algorithm, the enhancementalgorithm comprising instructions executable by the enhancementcontroller for enhancing the parameter of the at least one pixel.

According to still further embodiment of the present invention, theprobability function associated with at least one pixel is calculatedfrom the (y, u, v) color values associated with the at least one pixel.

The foregoing has outlined rather broadly the features and technicaladvantages of the present invention so that those skilled in the art maybetter understand the detailed description of the invention thatfollows. Additional features and advantages of the invention will bedescribed hereinafter that form the subject of the claims of theinvention. Those skilled in the art should appreciate that they mayreadily use the conception and the specific embodiment disclosed as abasis for modifying or designing other structures for carrying out thesame purposes of the present invention. Those skilled in the art shouldalso realize that such equivalent constructions do not depart from thespirit and scope of the invention in its broadest form.

Before undertaking the DETAILED DESCRIPTION, it may be advantageous toset forth definitions of certain words and phrases used throughout thispatent document: the terms “include” and “comprise,” as well asderivatives thereof, mean inclusion without limitation; the term “or,”is inclusive, meaning and/or; the phrases “associated with” and“associated therewith,” as well as derivatives thereof, may mean toinclude, be included within, interconnect with, contain, be containedwithin, connect to or with, couple to or with, be communicable with,cooperate with, interleave, juxtapose, be proximate to, be bound to orwith, have, have a property of, or the like; and the term “controller”means any device, system or part thereof that controls at least oneoperation, such a device may be implemented in hardware, firmware orsoftware, or some combination of at least two of the same. It should benoted that the functionality associated with any particular controllermay be centralized or distributed, whether locally or remotely.Definitions for certain words and phrases are provided throughout thispatent document, those of ordinary skill in the art should understandthat in many, if not most instances, such definitions apply to prior, aswell as future uses of such defined words and phrases.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention, and theadvantages thereof, reference is now made to the following descriptionstaken in conjunction with the accompanying drawings, wherein likenumbers designate like objects, and in which:

FIG. 1 is a block diagram of a television set that contains an apparatusfor segmenting and enhancing a video image according to principles ofthe present invention;

FIG. 2 illustrates the post-processing circuitry in the exemplarytelevision set in greater detail according to one embodiment of thepresent invention;

FIG. 3 illustrates an exemplary PC-based image processing system inaccordance with one embodiment of the present invention; and

FIG. 4 is a flow diagram illustrating the operation of the selectedportions of post processing circuitry according to one embodiment of thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

FIGS. 1 through 4, discussed below, and the various embodiments setforth in this patent document to describe the principles of theapparatus and method of the present invention are by way of illustrationonly and should not be construed in any way to limit the scope of theinvention. Those skilled in the art will understand that the principlesof the present invention may be implemented in any suitably arrangedvideo processing system, including, without limitation, televisionreceivers, television broadcast systems, personal computers (PCs)containing advanced video processing circuits and related videoprocessing software, and the like. In the descriptions that follow, avideo image sharpening apparatus according to the present invention isimplemented in a television set and in a personal computer (PC) forillustration purposes only.

FIG. 1 is a block diagram of television set 100, which contains anapparatus for segmenting and enhancing a video image according toprinciples of the present invention. Television set 100 comprisesantenna 105, television receiver 110, and display unit 115. Antenna 105receives incoming radio frequency (RF) television signals that areprocessed by television receiver 110. Display unit 115 may be, forexample, a cathode ray tube, a flat panel display, or any other type ofequipment for displaying video images.

Television receiver 110 comprises tuner 120, intermediate frequency (IF)processor 125, optional MPEG decoder 130, and post-processing circuitry140. MPEG decoder 130 (shown in dotted lines) is optional in theexemplary embodiment because television receiver 110 may be an analogtelevision receiver that does not contain an MPEG decoder. In such anembodiment, the output of IF processor 125 is used directly bypost-processing circuitry 140. Tuner 120 down-converts the incoming RFsignal to produce an intermediate frequency (IF) signal. The IF outputof tuner 120 is further down-converted by IF processor 125 to produce abaseband signal that may be, for example a transport stream. MPEGdecoder 130 may comprise a demultiplexer circuit that extracts from thetransport stream at least one elementary stream, such as an MPEG-encodeddata stream. MPEG decoder 130 then converts the encoded MPEG data streamand generates a standard video signal capable of being displayed bydisplay unit 115. However, in order to further improve the quality ofthe video signal generated by MPEG decoder 130, the output of MPEGdecoder 130 is transferred to post-processing circuitry 140 foradditional processing. The improved video signal at the output ofpost-processing circuitry 140 is then transmitted to display unit 115.

Post-processing circuitry 140 is capable of carrying out severaldifferent types of video signal processing. Exemplary video signalprocessing functions performed by post-processing circuitry 140 mayinclude: noise reduction algorithms, color correction, scaling,scan-rate conversion, adaptive feature enhancement, and other adaptiveobject based algorithms. In an advantageous embodiment, post-processingcircuitry 140 comprises segmentation circuitry and color enhancingcircuitry capable of performing soft segmentation and adaptive colorenhancement according to the principles of the present invention.

FIG. 2 illustrates post-processing circuitry 140 in greater detailaccording to one embodiment of the present invention. Post-processingcircuitry 140 comprises input frame buffer 210, image processor 220,memory 230, and output frame buffer 240. Post-processing circuitry 140receives incoming video frames from optional MPEG decoder 130 or IFprocessor 125 (as the case may be) and stores the pixel data of eachvideo frame in input frame buffer 210. Next, image processor 220performs soft segmentation of each video frame (as explained below ingreater detail) in accordance with the principles of the presentinvention.

Segmentation controller 222 comprises the portions of image processor220 that are capable of performing soft image segmentation. According toan advantageous embodiment of the present invention, segmentationcontroller 222 performs segmentation by executing instructions stored insegmentation algorithm 232 in memory 230. Enhancement controller 224comprises the portions of image processor 220 that are capable ofperforming one or more types of image segmentation (i.e., colorshifting, increasing color saturation, edge enhancing, and the like).According to an advantageous embodiment of the present invention,enhancement controller 222 performs these image enhancement techniquesby executing instructions stored in enhancement algorithm 234 in memory230. The segmented and enhanced video frames are then stored in outputfarm buffer 240 for subsequent transfer to display 115.

It was noted above that the present invention may be implemented in anysuitably arranged image processing system, including personal computerscontaining advanced video processing circuits and related videoprocessing software. This being the case, the present invention may beimplemented as computer-executable instructions and data stored on thehard disk drive of a PC or on removable storage medium, which may be forexample, a CD-ROM disk, a DVD disk, a 3.5 inch floppy disk, or the like.

FIG. 3 illustrates exemplary image processing system 300 in accordancewith one embodiment of the present invention. Image processing system300 comprises personal computer (PC) 310, external databases 380,monitor 385, and user devices 390. Personal computer 310 performssegmentation and enhancement of video frames retrieved from video files.External databases 380 comprise one or more sources from which digitizedvideo images may be retrieved. These databases may be provided throughaccess with a local area network (LAN), wide area network (WAN),Internet, and/or other sources such as direct access to data throughexternal devices such as tape, disk, or other storage devices.

Monitor 385 displays the enhanced video images. User device(s) 390represents one or more peripheral devices that may be manipulated by theuser of image processing system 300 to provide user inputs for thesystem. Typical peripheral user input devices include a computer mouse,a keyboard, a light pen, a joystick, a touch-table and associatedstylus, or any other device that may selectively be used to enter, toselect, and to manipulate data, including all or portions of theretrieved image(s). User device(s) 390 may also include output devices,such as a color printer, which can be utilized to capture a particularretrieved or modified image.

Personal computer 310 comprises image processor 320, random accessmemory (RAM) 330, disk storage 340, user input/output (I/O) card 350,video card 360, I/O interface 370, and processor bus 375. RAM 330further comprises image segmentation application 332 and imageenhancement application 334. Processor bus 375 transfers data betweenall of the components of personal computer 110. Image processor 320provides over-all control for personal computer 110 and performs softsegmentation of video images according to the principles of the presentinvention. Image processor 320 also performs color enhancement, edgesharpening and other enhancements in accordance with the principles ofthe present invention. The requirements and capabilities for imageprocessor 320 are well known in the art and need not be described ingreater detail other than as required for the present invention.

RAM 330 provides random access memory for temporary storage of dataproduced by personal computer 310, which is not otherwise provided bycomponents within the system. RAM 330 includes memory for segmentationapplication 332, enhancement application 334, as well as other memoryrequired by image processor 320 and associated devices. Segmentationapplication 332 represents the portion of RAM 330 in which the initialvideo image and any modified region-based images are temporarily storedduring the soft segmentation process. Segmentation application 332comprises executable instructions that define and segment regions andshapes of the same color, the same texture, a particular shape, anamplitude range or a temporal variation. Enhancement application 334comprises executable instructions in an application program executed byimage processor 320 that perform different types of enhancements on thesegments defined by segmentation application 334. Segmentationapplication 332 and enhancement application 334 may also be embodied asa program on a CD-ROM, computer diskette, or other storage media thatmay be loaded into a removable disk port in disk storage 340 orelsewhere, such as in external databases 380.

Disk storage 340 comprises one or more disk systems, including aremovable disk, for permanent storage of application programs, includingsegmentation application 332 and enhancement application 334, and otherdata. User I/O card 350 is an interface between user device(s) 390 andthe rest of personal computer 310. Video card 360 provides the interfacebetween monitor 385 and the rest of personal computer 310 and I/Ointerface 370 provides an interface between external databases 380 andthe rest of personal computer 310.

The present invention combines segmentation and local enhancement toprovide new enhancement functionality that has not been available in theprior art. For example, consider images featuring vegetation such asgrass, trees and other green plants. The present invention includes analgorithm that recognizes all regions of each image that consists ofgreen plants. The present invention then applies image processing deemedoptimum to green plants to these regions only. Other parts of the imagewould get enhancement treatments uniquely optimized for their features.

The present invention introduces the concept of soft segmentation, whichdefines a continuous (i.e., non-binary) function that models theprobability that a range of pixels lies within a desired segment. Suchsegments could be predefined pixel value ranges for the colors andtextures of, for example, plants, sky, human skin, and the like.Segments are defined according to the probability that a group of pixelsare part of the same segment.

After the segments are defined, the amount of enhancement that isapplied is also a function of the probability measurement. The greaterthe probability that a pixel lies within a segment, the greater theamount of enhancement that is applied to that pixel. Maximum enhancementis applied where the probability is maximum. Since the probability islower near the edges of a segment, the enhancement fades out gracefullyat the edges of the segment. This allows for such segmentation-basedenhancements to be applied to moving images without the frame-to-frameartifacts attributed to hard (or binary) segmentation.

According to an advantageous embodiment of the present invention, onesuitable probability model for many soft segmentation tasks is theGaussian distribution. However, the efficacy of the soft segmentationmodel would hold for other mathematical distribution functions as well.According to one embodiment of the present invention, a probabilityfunction may be defined in the hue-saturation-value (HSV) color space orin the YUV color space. While the invention covers the use of these orany other color space for specifying color properties, the YUV colorspace is especially desirable, since TV signals are already available inYUV form and no further transformation to another color space isrequired. A three dimensional Gaussian distribution function may be usedto model the probability for soft segmentation. This function is in theform of:P(y,u,v)=e ^(z),whereZ=(−A ² +B ² +C ²);A=(y−y _(MID))/σ_(y);B=(u−u _(MID))/σ_(u); C=(v−v _(MID))/σ_(v),for 0<y<255, 0<u<255, 0<v<255.

A set of exemplary parameter values may comprise:

-   y_(MID)=102-   u_(MID)=106-   v_(MID)=108-   σ_(y)=89-   σ_(u)=19-   σ_(v)=19

In the case of plant segments, an exemplary enhancement algorithm mayshift the color of the plant segment toward the color of bright greengrass, increase the color saturation, increase the luminance and applyedge enhancement. The amount of enhancement that is applied isproportional to the probability function. The concepts described hereare not restricted to the plant segmentation given as a sampleapplication. Other regions such as sky, human skin, buildings, and thelike may require different probability functions and different parametervalues.

FIG. 4 depicts flow diagram 400, which illustrates the operation ofselected portions of post-processing circuitry 140 according to oneembodiment of the present invention. During routine operation,post-processing circuitry 140 receives video frames from MPEG decoder130 and stores them in input frame buffer 210. Image processor 220 thencalculates the probability function described above for all pixels ineach frame (process step 405). Next, image processor 220 performssegmentation by comparing the pixel probabilities to predefined valuesof common objects, such as the sky, different types of human skin,grass, and the like (process step 410). Groups of pixels that comparefavorably with the predefined values are identified as belonging in acommon segment. Alternatively, other known prior art segmentationtechniques may be used in addition to, or in place of, segmentationbased on the above-described probability function (process step 415).

Once the frames are segmented, image processor 220 performs one or morevideo enhancement techniques on the segmented vide frames according tothe probability function associated with each pixel. According to theprinciples of the present invention, the amount of enhancement isproportional to the probability function (process step 420). That is, ifa pixel has a relatively high probability of belonging to a certainsegment, then a relatively greater amount of enhancement is applied.Conversely, if a pixel has a relatively low probability of belonging toa certain segment, then a relatively smaller amount of enhancement isapplied. For example, the green pixels within the boundaries of a palmleaf that is defined as a region have a greater probability value thanpixels near the edge, which may be transitioning to another color as thepalm leaf moves. Thus, a color enhancement technique that increases thegreen coloration of the palm leaf would apply a greater amount of colorenhancement near the center of the palm leaf than at the edge of thepalm leaf. Finally, the segmented and enhanced video frames aretransferred to display 115 or, alternatively, to a storage device in apersonal computer embodiment of the present invention.

Although the present invention has been described in detail, thoseskilled in the art should understand that they can make various changes,substitutions and alterations herein without departing from the spiritand scope of the invention in its broadest form.

1. An apparatus for performing segmentation-based enhancements of avideo image, said apparatus comprising: an input buffer for storingvideo frames of an incoming video signal; a segmentation controllercapable of segmenting a first stored frame into a plurality of segments,each of said plurality of segments comprising a plurality of pixelshaving at least one common property; an image processor capable ofcalculating a probability function associated with at least one pixel insaid first stored frame, said probability function indicating aprobability that said at least one pixel belongs within a first selectedone of said plurality of segments; and an enhancement controller capableof enhancing a parameter of said at least one pixel as a function ofsaid probability function of said at least one pixel.
 2. The apparatusas set forth in claim 1 wherein said segmentation controller segmentssaid first stored frame into said plurality of segments as a function ofsaid probability function.
 3. The apparatus as set forth in claim 2wherein said enhancement controller increases an amount of enhancementof said parameter as a value of said probability function increases. 4.The apparatus as set forth in claim 3 wherein said enhancementcontroller decreases an amount of enhancement of said parameter as avalue of said probability function decreases.
 5. The apparatus as setforth in claim 1 further comprising a memory capable of storing asegmentation algorithm, said segmentation algorithm comprisinginstructions executable by said segmentation controller for segmentingsaid first stored frame into said plurality of segments.
 6. Theapparatus as set forth in claim 5 wherein said memory is further capableof storing an enhancement algorithm, said enhancement algorithmcomprising instructions executable by said enhancement controller forenhancing said parameter of said at least one pixel.
 7. The apparatus asset forth in claim 1 wherein said probability function associated withat least one pixel is calculated from the (y,u,v) color valuesassociated with said at least one pixel.
 8. A television receivercomprising: demodulation circuitry capable of receiving an incoming RFtelevision signal and generating therefrom a baseband video signalcapable of being displayed as a plurality of pixels on a video display;and post processing circuitry, coupled to an output of said demodulationcircuitry and receiving therefrom said baseband video signal, capable ofperforming segmentation-based enhancements of a video image, said postprocessing circuitry comprising: an input buffer for storing videoframes of an incoming video signal; a segmentation controller capable ofsegmenting a first stored frame into a plurality of segments, each ofsaid plurality of segments comprising a plurality of pixels having atleast one common property; an image processor capable of calculating aprobability function associated with at least one pixel in said firststored frame, said probability function indicating a probability thatsaid at least one pixel belongs within a first selected one of saidplurality of segments; and an enhancement controller capable ofenhancing a parameter of said at least one pixel as a function of saidprobability function of said at least one pixel.
 9. The televisionreceiver as set forth in claim 8 wherein said segmentation controllersegments said first stored frame into said plurality of segments as afunction of said probability function.
 10. The television receiver asset forth in claim 9 wherein said enhancement controller increases anamount of enhancement of said parameter as a value of said probabilityfunction increases.
 11. The television receiver as set forth in claim 10wherein said enhancement controller decreases an amount of enhancementof said parameter as a value of said probability function decreases. 12.The television receiver as set forth in claim 8 further comprising amemory capable of storing a segmentation algorithm, said segmentationalgorithm comprising instructions executable by said segmentationcontroller for segmenting said first stored frame into said plurality ofsegments.
 13. The television receiver as set forth in claim 12 whereinsaid memory is further capable of storing an enhancement algorithm, saidenhancement algorithm comprising instructions executable by saidenhancement controller for enhancing said parameter of said at least onepixel.
 14. The television receiver as set forth in claim 8 wherein saidprobability function associated with at least one pixel is calculatedfrom the (y,u,v) color values associated with said at least one pixel.15. A method of performing segmentation-based enhancements of a videoimage comprising the steps of: storing video frames of an incoming videosignal in an input buffer; segmenting a first stored frame into aplurality of segments, each of the plurality of segments comprising aplurality of pixels having at least one common property; calculating aprobability function associated with at least one pixel in the firststored frame, the probability function indicating a probability that theat least one pixel belongs within a first selected one of the pluralityof segments; and enhancing a parameter of the at least one pixel as afunction of the probability function of the at least one pixel.
 16. Themethod as set forth in claim 15 wherein the step of segmenting segmentsthe first stored frame into the plurality of segments as a function ofthe probability function.
 17. The method as set forth in claim 16wherein the step of enhancing increases an amount of enhancement of theparameter as a value of the probability function increases.
 18. Themethod as set forth in claim 17 wherein the step of enhancing decreasesan amount of enhancement of the parameter as a value of the probabilityfunction decreases.
 19. Computer-executable instructions stored on acomputer-readable storage medium and capable of performingsegmentation-based enhancements of a video image, thecomputer-executable instructions comprising the steps of: storing videoframes of an incoming video signal in an input buffer; segmenting afirst stored frame into a plurality of segments, each of the pluralityof segments comprising a plurality of pixels having at least one commonproperty; calculating a probability function associated with at leastone pixel in the first stored frame, the probability function indicatinga probability that the at least one pixel belongs within a firstselected one of the plurality of segments; and enhancing a parameter ofthe at least one pixel as a function of the probability function of theat least one pixel.
 20. The computer-executable instructions stored on acomputer-readable storage medium as set forth in claim 19 wherein thestep of segmenting segments the first stored frame into the plurality ofsegments as a function of the probability function.
 21. Thecomputer-executable instructions stored on a computer-readable storagemedium as set forth in claim 20 wherein the step of enhancing increasesan amount of enhancement of the parameter as a value of the probabilityfunction increases.